“The good news is that established companies in a number of industries are already using big data to improve their current business practices and services. At the other end of the spectrum, Internet start-ups are using it to create a whole range of innovative products and business models,” says Bøe-Lillegraven.
“Add this up, and the publishing industry does not have to ‘re-invent the wheel’ to harness the power of big data analytics. Rather, they can adapt and apply existing best practices to their own business,” he says, pointing to the recent rise of Uber, the ride-sharing app, as a prominent example of how big data can completely change the playing field in well-established business.
“Big data is a game-changer, and you have to think about which team you want to be on: Do you want to be on the side of the legacy cab business, which is trying to block Uber out, or do you want to be a part of the new data-driven business world where anything is possible?”
Bøe-Lillegraven continues, “Having worked in the media business over the past 15 years, I have seen first-hand that really radical innovation is really difficult – particularly for large existing firms, who have to struggle with ingrained company structure, culture and traditional revenue streams. But there is another way of doing business, and we have to learn how to do it.”
But even as big data is attracting big media attention, it has already peaked on the Gartner “hype cycle,” which measures emerging technologies that are changing the digital business.
In 2013, 64 percent of companies surveyed globally said they were investing – or intending to invest – in big data technology. But while companies buy into the value of big data, many are struggling to actually get value from it.
Identifying and applying such big-data practices to the publishing industry is the goal of a research collaboration between WAN-IFRA and the Cambridge Service Alliance, a world-leading research centre on data-driven business models (or DDBM for short) at the University of Cambridge, U.K.
The research project was initiated by Bøe-Lillegraven, an experienced media and tech executive who is currently finishing his Ph.D. in big data analytics with a research stay at the University of Cambridge, where they work with leading companies from a range of industries, getting first-hand experience in both the opportunities and challenges associated with big data strategies.
Just having “big data” is not enough
Big data is certainly nothing new. Most organisations have vast amounts of data stored in different systems in a variety of formats. The real challenge lies in bringing those together in one place, where they can be combined in a meaningful way.
Dr. Mohamed ZakiOne problem is that firms tend to focus on the technological aspects of data collection, rather than thinking about how big data can create value, says Dr. Mohamed Zaki (left) of the Cambridge Service Alliance, an expert on data-driven business models.
“When publishing companies really started to get momentum with their online business around 2003, only about 5 exabytes (1 exabyte is 10 to the power of 18 bytes) of data had been cumulatively created by humankind. This same volume of data is now created every 48 hours and continues to grow at an astonishing rate,” says Zaki. “To get value out of big data, organisations need to be able to capture, store, analyse, visualise and interpret it – none of which is straightforward.
“We now live in a world where data is often described as ‘the new oil’. Just as with oil, the value contained within data is recognized universally, and the challenges are threefold: how to extract it, how to refine it and then how to ensure it is utilised most effectively,” he says.
According to Zaki, the Cambridge Service Alliance has been focused initially on how “pure” start-ups use data in radical new ways to drive new business.
While established publishing organisations may find it hard to move away from their entrenched ways of doing things, Internet start-ups have the luxury of being able to invent new business models at will. But the results of the research should help companies of all sizes – not just start-ups – understand how big data may be able to transform their businesses.
Filling the big data void
The WAN-IFRA big data project aims to address the apparent “big data void” by providing a foundation and structural guidelines within which existing publishing companies can analyse, construct and apply big data strategies.
“Our research suggests that firms are developing what we call ‘data-driven business models,’ where they create additional business value by extracting, refining, distributing, uncovering insights and ultimately capitalizing upon data,” says Zaki, who has identified six distinct types of data-driven business models:
- Free data collector and aggregator: Companies such as Gnip collect data from vast numbers of different, mostly free, sources, filter it, enrich it and supply it to customers in the format they want.
- Analytics-as-a-service: These are companies providing analytics, usually on data provided by their customers. Sendify, for example, provides businesses with real-time caller intelligence, so when a call comes in they see a whole lot of additional information relating to the caller that helps them maximise the sales opportunity.
- Data generation and analysis: These companies generate their own data through crowdsourcing, or through smartphones or other sensors. They may also provide analytics. Examples include Go-Squared, Mixpanel and Spinnakr, which collect data by using a tracking code on their customers’ websites, analyse the data, and report on it using a web interface.
- Free data knowledge discovery: The model here is to take freely available data and analyse it. Gild, for example, helps companies recruit developers by automatically evaluating the code they publish and scoring it.
- Data-aggregation-as-a-service: These companies aggregate data from multiple internal sources for their customers, then present it back to them through a range of user-friendly, often highly visual interfaces. In the education sector, Always Prepped helps teachers monitor their students’ performance by aggregating data from multiple education programmes and websites.
- Multi-source data mash-up and analysis: These companies aggregate data provided by their customers with other external, mostly free, data sources, and perform analytics on this data to enrich or benchmark customer data. Welovroi is a web-based digital marketing, monitoring and analysing tool that enables companies to track a large number of different metrics. It also integrates external data and allows benchmarking of the success of marketing campaigns.
Which of these business models may be most appropriate for the publishing industry remains to be seen. But there is no question that agile and innovative start-ups are creating entirely new business models based on big data and becoming hugely successful at it. These models can also inspire established publishing companies to think about new ways in which they can capture value from their data. The outcome of the WAN-IFRA big data project will be a research-validated and industry-focused innovation framework that publishers can utilise to construct their own big data-driven business models – large or small.
Big data also will be a big topic at the upcoming WAN-IFRA Digital Media Europe conference in London (20-22 April).